Lexustherealone

Model Specification: Importance of correctly specifying the functional form and dealing with omitted variable bias. Dummy Variables: Use of binary variables in regression models to capture qualitative effects

Regression Analysis: Simple and multiple linear regressions, understanding the Ordinary Least Squares (OLS) estimator, assumptions of the Classical Linear Regression Model (CLRM), and how to interpret coefficients. Hypothesis Testing: Null and alternative hypotheses, t-tests, F-tests, p-values, and confidence intervals.